Agent-Based Modeling of Culture's Consequences for Trade

Abstract

In this thesis, culture is interpreted as a property of a group of people who share the meaning they attach to symbols, have a common way of expressing their opinions and feelings, and share value systems to judge what is good or bad. The unwritten rules of a culture govern the interpretation of observations and emotions and how to react appropriately. The rules are embedded in an individuals’ mind, form childhood on, by interactions with group members. People often are not aware of differences between their own unwritten rules and those of people having a different cultural background. This may result in unwarranted distrust or unwarranted trust, with serious consequences for the future of relationships. Cultural differences are known to have their effects on trade. Signals that indicate benevolence and trustworthiness of a trade partner in one’s own culture may be interpreted differently by people having a different cultural background. Hofstede (2001) has identified five dimensions of cultural differences: ? Given ingroup relation with relatives and community members may have a different impact on professional relationships in different cultures. ? The impact of hierarchical relationships on the freedom of action of trade partners may be different across cultures. ? Some cultures are oriented toward cooperation and care-taking; others are oriented toward performance and competition. ? Xenophobia is a wide-spread phenomenon in some cultures, while people in other cultures may be more open to the unknown. ? In some cultures people are anxious to keep up their status and display their societal success, while in other cultures thrift and perseverance are seen as virtues. Cultural differences may have their effects in trade on the acceptability of potential partners, on progress and success of negotiations, and on the extent to which partners live up to the negotiated contracts. In a research project Meijer (2009) developed a gaming simulation to study the role of trust in supply networks of food products. The game is called the TRUST & TRACING game. In this game, the producers are informed about product quality. The other players either have to trust the suppliers on their quality statements, or they can have the products traced by an independent authority, but the latter will cost them a fee. In addition to the financial considerations, they must take into account that showing distrust may bring damage to their relationships. Experiments with human subjects in different cultures have shown that the considerations lead to different actions in different countries. It was also found that the inclination to grab an opportunity to defect was different across countries. The subject of this thesis is a computer simulation of the TRUST & TRACING GAME. The purposes of the computer simulation are: ? Validation of theories about, implemented in models of, the players’ behaviors ? testing of hypotheses about relations of rules of the game and parameters of individual players with aggregated game statistics, ? the design of useful game configurations to be played with human players. In the computer simulation the players’ rolls are realized by software agents. The questions which are answered in this thesis concern the modeling of culture’s consequences for the decisions taken by the agents. Such an agent is a computer program which simulates the behavior of human players. In a multi-agent simulation a group of software agents is acting and interacting simultaneously. Autonomy is an important property of software agents. The agents decide what to do; there is no central computer program that imposes decisions on them. Important functions of agents in the present simulation are to approach new potential trade partners, to negotiate about a transaction and to exchange proposals, and, when the negotiation has ended successfully, to exchange products, and to decide and request a trace to be performed. The agents’ decision mechanisms are implemented according to models and data available from scientific literature. To model the influence of culture on the decision making, an expert systems approach is taken, using the Synthetic Cultures according to Hofstede en Pedersen (1999). To develop an expert system, knowledge engineers represent knowledge about some domain of application as a set of rules that can be interpreted by a computer system. Since culture is considered as a set of rules, such an approach is a natural way to model it. The development of expert systems always is an interdisciplinary project. In this case the work of Geert Hofstede has been used and an expert on this work and on Synthetic Cultures has been involved in the formulation of the rules. Synthetic Cultures are imaginary cultures in which the effects of a single dimension of culture are emphasized, isolated from the effects of the other dimensions. The purpose is to make the differences related to that dimension teachable. In reality the differences may be less pronounced and may be mixed with differences related with the other dimensions. In this thesis an approach has been elaborated to compute the simultaneous effect of several dimensions. The approach is based on the principle of weak disjunction, which implies that, if several dimensions have a similar effect, only the strongest effects counts. For instance, if dimension A would have an effect of 75% and dimension B would have an effect of 25%, then their simultaneous effect would be 75%. Expert systems must at least have face validity. An expert in the domain of application mustaccept the decisions that the system produces and the reasoning that leads to these decisions, as being believable. For this purpose computations for specific cases can be made, of which the results are judged by the expert. Further, the results of sensitivity analysis can be judged by an expert. Sensitivity analysis of a model is performed by studying how model outputs vary in relation with systematic variation of input parameter. In addition to face validity, the model must be tested empirically. To that end outputs from gaming simulations with human participants can be compared with outputs from multi-agent simulations. For example, Meijer et al. (2006) found different outcomes from the TRUST & TRACING game between games played in the United States and in the Netherlands. Compared with the Dutch, American players are found to be more eager to buy top quality products, have a stronger inclination to opportunism, anticipate to a greater extent on their partners to defect, and have a stronger preference for quality certification. These differences where reproduced by the multi-agent simulation. The main question of this research is, whether an expert systems approach is feasible to develop a valid model of cultural differentiation in multi-agent simulations, to be applied in research with gaming simulations. The conclusions are: 1. Effects of dimensions of culture can be modeled as an expert system based on Synthetic Cultures. Modeling the simultaneous effects of several dimensions as an expert system proved not feasible: the complexity exceeded the intellectual powers of both expert and modeler. 2. The simultaneous effect of several dimensions can be modeled by weak disjunction of effects. The results have face validity and have empirically been verified for a limited number of cases. 3. Sensitivity analysis of this model is a complex undertaking if both cultural parameters and other parameters are simultaneously varied, because of the strong interactions between these types of parameters. When only the culture parameters are varied (with a fixed setting of the other parameters), or only the other parameters are varied (in a fixed cultural setting), straightforward sensitivity analysis is feasible. Furthermore, it was found that the sensitivity of aggregate model outputs may greatly differ from sensitivity of individual level outputs: parameters that do not affect the aggregate system performance, may affect results of individual agents. 4. This thesis proves that multi-agent simulation is a potent instrument to be used in research with gaming simulations, in particular for the purpose of validation of behavioral models. A problematic issue is, that similarity of the outputs of gaming simulations and multi-agent simulations is no sound proof that the agent correctly implements the human decision making mechanism. This issue is known as under-determination. A validation method is proposed, which builds on the model’s composed structure. Under-determination can be avoided by separate validation of the components in micro-games. The results of this research contribute to the methodology of cultural adaptation of intelligent software agents. This is relevant for the development of research instruments (like the TRUST & TRACING game), educational and training applications to make people aware of cultural differences, and affective human-computer interfaces in a globalizing world.